One significant factor we expect the video representation learning to capture, especially in contrast with the image representation learning, is the object motion. However, we found that in the current mainstream video datasets, some action categorie...
Database virtualization is the decoupling of the database layer, which lies between the storage and application layers within the application stack. Virtualization
We review the distortions of spectra of relic neutrinos due to the interactions with electrons, positrons, and neutrinos in the early universe. We solve integro-differential kinetic equations for the neutrino density matrix, including vacuum three-fl...
Knowledge distillation is an effective and hardware-friendly method, which plays a key role in lightweighting remote sensing object detection. However, existing distillation methods often encounter the issue of mixed features in remote sensing images...
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Recently significant progress has been made in human action recognition and behavior prediction using deep learning techniques, leading to improved vision-based semantic understanding. However, there is still a lack of high-quality motion datasets fo...
In our previous paper, the concept of sub-symmetry of a differential system was introduced, and its properties and some applications were studied. It was shown that sub-symmetries are important in decoupling a differential system, and in the deformat...
A new model for general cyclical long memory is introduced, by means of random modulation of certain bivariate long memory time series. This construction essentially decouples the two key features of cyclical long memory: quasi-periodicity and long-t...
We present a study of the late-time interaction between supermassive black hole binaries and retrograde circumbinary disks during the period of gravitational wave-driven inspiral. While mergers in prograde disks have received extensive study, retrogr...
Temporal embryo images and parental fertility table indicators are both valuable for pregnancy prediction in \textbf{in vitro fertilization embryo transfer} (IVF-ET). However, current machine learning models cannot make full use of the complementary...
In the present study, for the first time, an effort sharing approach based on Inertia and Capability principles is proposed to assess European Union (EU27) carbon budget distribution among the Member States. This is done within the context of achievi...
Credential brokers offer a way to separate identity from access in CI/CD systems. This paper shows how verifiable identities issued at runtime, such as those from SPIFFE, can be used with brokers to enable short-lived, policy-driven credentials for p...
We study the relationship between supermassive black hole (BH) feedback, BH luminosity and the kinematics of stars and gas for galaxies in IllustrisTNG. We use a sample of galaxies with mock MaNGA observations to identify kinematic misalignment at $z...
Federated Learning (FL) allows edge devices to collaboratively learn a shared prediction model while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to store data in the cloud. Despite th...
Online forums are rich sources of information about user communication activity over time. Finding temporal patterns in online forum communication threads can advance our understanding of the dynamics of conversations. The main challenge of temporal...
Reduction in power consumption has become a major criterion of design in modern ICs. One such scheme to reduce power consumption by an IC is the use of multiple power supplies for critical and non-critical paths. To maintain the impedance of a powe...
Multi-turn dialogue modeling as a challenging branch of natural language understanding (NLU), aims to build representations for machines to understand human dialogues, which provides a solid foundation for multiple downstream tasks. Recent studies of...
The official code of our paper at EMNLP 2022: Back to the Future: Bidirectional Information Decoupling Network for Multi-turn Dialogue Modeling (⭐ 16)
Federated Learning (FL) has emerged as a promising technique for edge devices to collaboratively learn a shared prediction model, while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to...
This paper presents a formal analysis of the Lightning Network as a monetary system structurally diverging from Bitcoin's base-layer settlement model. We demonstrate that under increasing transaction demand, BTC transaction fees rise superlinearly du...